Wnt Signaling–Related Osteokines at Rest and Following Plyometric Exercise in Prepubertal and Early Pubertal Boys and Girls
Bibliographic record
Abstract
Purpose: This study examined osteokines related to Wnt signaling at rest and in response to plyometric exercise in 12 boys [10.2 (0.4) y] and 12 girls [10.5 (0.4) y]. Methods: One resting (preexercise) and 3 postexercise (5 min, 1 h, and 24 h) blood samples were analyzed for sclerostin, dickkopf-related protein 1 (DKK-1), osteoprotegerin (OPG), and receptor activator of nuclear factor kappa-β ligand (RANKL). Results: Girls had higher resting sclerostin than boys [187.1 (40.1) vs 150.4 (36.4) pg·mL−1, respectively; P = .02]. However, boys had higher DKK-1 [427.7 (142.3) vs 292.8 (48.0) pg·mL−1, respectively; P = .02] and RANKL [3.9 (3.8) vs 1.0 (0.4) pg·mL−1, respectively; P < .01] than girls. In girls, sclerostin significantly decreased 5-minute and 1-hour postexercise (χ2 = 12.7, P = .01), and RANKL significantly decreased 5-minute postexercise (χ2 = 19.1, P < .01) and continued to decrease up to 24-hour postexercise, with large effect sizes. In boys, DKK-1 significantly decreased 1-hour postexercise and remained lower than preexercise 24-hour postexercise (χ2 = 13.0, P = .01). OPG increased in both boys (χ2 = 13.7, P < .01) and girls (χ2 = 11.4, P = .01), with boys having significantly higher OPG at 5-minute and 1-hour postexercise, whereas in girls, this increase was only seen 24-hour postexercise. Conclusion: Plyometric exercise induces an overall anabolic osteokine response favoring osteoblastogenesis over osteoclastogenesis in both boys and girls although the timeline and mechanism(s) may be different.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".